Carolina Ferreira Nicoletti1, Carla Barbosa Nonino2, Bruno Affonso Parenti de Oliveira3, Marcela Augusta de Souza Pinhel4, Maria Luisa Mansego5, Fermin Ignacio Milagro6,7,8, Maria Angeles Zulet9,10,11,12, José Alfredo Martinez13,14,15,16. 1. Department of Internal Medicine, Faculty of Medicine of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil. carol_nicolettif@yahoo.com.br. 2. Department of Internal Medicine, Faculty of Medicine of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil. carla@fmrp.usp.br. 3. Department of Internal Medicine, Faculty of Medicine of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil. bruno_parenti@hotmail.com. 4. Department of Internal Medicine, Faculty of Medicine of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil. marcelapinhel@yahoo.com.br. 5. Department of Nutrition, Food Science and Physiology, University of Navarra, c/Irunlarrea 1, 31008, Pamplona, Spain. mlmansego@unav.es. 6. Department of Nutrition, Food Science and Physiology, University of Navarra, c/Irunlarrea 1, 31008, Pamplona, Spain. fmilagro@unav.es. 7. Centre for Nutrition Research, University of Navarra, Pamplona, Spain. fmilagro@unav.es. 8. CIBERobn Fisiología Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III, Madrid, Spain. fmilagro@unav.es. 9. Department of Nutrition, Food Science and Physiology, University of Navarra, c/Irunlarrea 1, 31008, Pamplona, Spain. mazulet@unav.es. 10. Centre for Nutrition Research, University of Navarra, Pamplona, Spain. mazulet@unav.es. 11. CIBERobn Fisiología Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III, Madrid, Spain. mazulet@unav.es. 12. IdiSNA, Navarra Institute for Health Research, Pamplona, Spain. mazulet@unav.es. 13. Department of Nutrition, Food Science and Physiology, University of Navarra, c/Irunlarrea 1, 31008, Pamplona, Spain. jalfmtz@unav.es. 14. Centre for Nutrition Research, University of Navarra, Pamplona, Spain. jalfmtz@unav.es. 15. CIBERobn Fisiología Obesidad y Nutrición (CIBERobn), Instituto de Salud Carlos III, Madrid, Spain. jalfmtz@unav.es. 16. IdiSNA, Navarra Institute for Health Research, Pamplona, Spain. jalfmtz@unav.es.
Abstract
BACKGROUND: Weight loss can be influenced by genetic factors and epigenetic mechanisms that participate in the regulation of body weight. This study aimed to investigate whether the weight loss induced by two different obesity treatments (energy restriction or bariatric surgery) may affect global DNA methylation (LINE-1) and hydroxymethylation profile, as well as the methylation patterns in inflammatory genes. METHODS: This study encompassed women from three differents groups: 1. control group (n = 9), normal weight individuals; 2. energy restriction group (n = 22), obese patients following an energy-restricted Mediterranean-based dietary treatment (RESMENA); and 3. bariatric surgery group (n = 14), obese patients underwent a hypocaloric diet followed by bariatric surgery. Anthropometric measurements and 12-h fasting blood samples were collected before the interventions and after 6 months. Lipid and glucose biomarkers, global hydroxymethylation (by ELISA), LINE-1, SERPINE-1, and IL-6 (by MS-HRM) methylation levels were assessed in all participants. RESULTS: Baseline LINE-1 methylation was associated with serum glucose levels whereas baseline hydroxymethylation was associated with BMI, waist circumference, total cholesterol, and triglycerides. LINE-1 and SERPINE-1 methylation levels did not change after weight loss, whereas IL-6 methylation increased after energy restriction and decreased in the bariatric surgery group. An association between SERPINE-1 methylation and weight loss responses was found. CONCLUSIONS: Global DNA methylation and hydroxymethylation might be biomarkers for obesity and associated comorbidities. Depending on the obesity treatment (diet or surgery), the DNA methylation patterns behave differently. Baseline SERPINE-1 methylation may be a predictor of weight loss values after bariatric surgery.
BACKGROUND:Weight loss can be influenced by genetic factors and epigenetic mechanisms that participate in the regulation of body weight. This study aimed to investigate whether the weight loss induced by two different obesity treatments (energy restriction or bariatric surgery) may affect global DNA methylation (LINE-1) and hydroxymethylation profile, as well as the methylation patterns in inflammatory genes. METHODS: This study encompassed women from three differents groups: 1. control group (n = 9), normal weight individuals; 2. energy restriction group (n = 22), obesepatients following an energy-restricted Mediterranean-based dietary treatment (RESMENA); and 3. bariatric surgery group (n = 14), obesepatients underwent a hypocaloric diet followed by bariatric surgery. Anthropometric measurements and 12-h fasting blood samples were collected before the interventions and after 6 months. Lipid and glucose biomarkers, global hydroxymethylation (by ELISA), LINE-1, SERPINE-1, and IL-6 (by MS-HRM) methylation levels were assessed in all participants. RESULTS: Baseline LINE-1 methylation was associated with serum glucose levels whereas baseline hydroxymethylation was associated with BMI, waist circumference, total cholesterol, and triglycerides. LINE-1 and SERPINE-1 methylation levels did not change after weight loss, whereas IL-6 methylation increased after energy restriction and decreased in the bariatric surgery group. An association between SERPINE-1 methylation and weight loss responses was found. CONCLUSIONS: Global DNA methylation and hydroxymethylation might be biomarkers for obesity and associated comorbidities. Depending on the obesity treatment (diet or surgery), the DNA methylation patterns behave differently. Baseline SERPINE-1 methylation may be a predictor of weight loss values after bariatric surgery.
Entities:
Keywords:
5-hmC hydroxymethylation; DNA methylation; LINE-1, IL-6, SERPINE-1; Obesity
Authors: Zhong-Zheng Zhu; Lifang Hou; Valentina Bollati; Letizia Tarantini; Barbara Marinelli; Laura Cantone; Allen S Yang; Pantel Vokonas; Jolanta Lissowska; Silvia Fustinoni; Angela C Pesatori; Matteo Bonzini; Pietro Apostoli; Giovanni Costa; Pier Alberto Bertazzi; Wong-Ho Chow; Joel Schwartz; Andrea Baccarelli Journal: Int J Epidemiol Date: 2010-09-15 Impact factor: 7.196
Authors: Luigi Bouchard; Rémi Rabasa-Lhoret; May Faraj; Marie-Eve Lavoie; Jonathan Mill; Louis Pérusse; Marie-Claude Vohl Journal: Am J Clin Nutr Date: 2009-11-25 Impact factor: 7.045
Authors: R Ara; L Blake; L Gray; M Hernández; M Crowther; A Dunkley; F Warren; R Jackson; A Rees; M Stevenson; K Abrams; N Cooper; M Davies; K Khunti; A Sutton Journal: Health Technol Assess Date: 2012 Impact factor: 4.014
Authors: Ryan Lister; Eran A Mukamel; Joseph R Nery; Mark Urich; Clare A Puddifoot; Nicholas D Johnson; Jacinta Lucero; Yun Huang; Andrew J Dwork; Matthew D Schultz; Miao Yu; Julian Tonti-Filippini; Holger Heyn; Shijun Hu; Joseph C Wu; Anjana Rao; Manel Esteller; Chuan He; Fatemeh G Haghighi; Terrence J Sejnowski; M Margarita Behrens; Joseph R Ecker Journal: Science Date: 2013-07-04 Impact factor: 47.728
Authors: Yen-Tsung Huang; Jennifer Z J Maccani; Nicola L Hawley; Rena R Wing; Karl T Kelsey; Jeanne M McCaffery Journal: Int J Obes (Lond) Date: 2014-12-18 Impact factor: 5.095
Authors: Mohsen Afarideh; Roman Thaler; Farzaneh Khani; Hui Tang; Kyra L Jordan; Sabena M Conley; Ishran M Saadiq; Yasin Obeidat; Aditya S Pawar; Alfonso Eirin; Xiang-Yang Zhu; Amir Lerman; Andre J van Wijnen; Lilach O Lerman Journal: Epigenetics Date: 2020-09-20 Impact factor: 4.528